Solid-state disks (SSDs) have the potential to revolutionize the storage system landscape. However, there is little published work about their internal organization or the design choices that SSD manufacturers face in pursuit of optimal performance. This paper presents a taxonomy of such design choices and analyzes the likely performance of various configurations using a trace-driven simulator and workload traces extracted from real systems. We find that SSD performance and lifetime is highly workloadsensitive, and that complex systems problems that normally appear higher in the storage stack, or even in distributed systems, are relevant to device firmware. 1

Flash solid state drives (SSDs) provide an attractive alternative to traditional magnetic hard disk drives (HDDs) for DBMS applications. Naturally there is substantial interest in redesigning critical database internals, such as join algorithms, for flash SSDs. However, we must carefully consider the lessons that we have learnt from over three decades of designing and tuning algorithms for magnetic HDD-based systems, so that we continue to reuse techniques that worked for magnetic HDDs and also work with flash SSDs. The focus of this paper is on recalling some of these lessons in the context of ad hoc join algorithms. Based on an actual implementation of four common ad hoc join algorithms on both a magnetic HDD and a flash SSD, we show that many of the “surprising ” results from magnetic HDD-based join methods also hold for flash SSDs. These results include the superiority of block nested loops join over sort-merge join and Grace hash join in many cases, and the benefits of blocked I/Os. In addition, we find that simply looking at the I/O costs when designing new flash SSD join algorithms can be problematic, as the CPU cost is often a bigger component of the total join cost with SSDs. We hope that these results provide insights and better starting points for researchers designing new join algorithms for flash SSDs. 1.